






"""simple docstring"""





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE   :							Optional[Any]          =		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   :							Tuple          =		{'''vocab_file''': '''spm_char.model'''}

_SCREAMING_SNAKE_CASE   :							List[Any]          =		{
    '''vocab_file''': {
        '''microsoft/speecht5_asr''': '''https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model''',
        '''microsoft/speecht5_tts''': '''https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model''',
        '''microsoft/speecht5_vc''': '''https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model''',
    }
}

_SCREAMING_SNAKE_CASE   :							str          =		{
    '''microsoft/speecht5_asr''': 1024,
    '''microsoft/speecht5_tts''': 1024,
    '''microsoft/speecht5_vc''': 1024,
}






class 	a		(   __snake_case						):
    SCREAMING_SNAKE_CASE		:	List[str]		=					VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE		:	int		=					PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE		:	str		=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE		:	List[Any]		=					["""input_ids""", """attention_mask"""]






    def __init__(			self	:				Tuple			,		__SCREAMING_SNAKE_CASE	:				Optional[int]			,		__SCREAMING_SNAKE_CASE	:				int="<s>"			,		__SCREAMING_SNAKE_CASE	:				Union[str, Any]="</s>"			,		__SCREAMING_SNAKE_CASE	:				str="<unk>"			,		__SCREAMING_SNAKE_CASE	:				str="<pad>"			,		__SCREAMING_SNAKE_CASE	:				Optional[Dict[str, Any]] = None			,		**__SCREAMING_SNAKE_CASE	:				List[Any]			,		)	->						None:
      lowerCamelCase_       	=		{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__SCREAMING_SNAKE_CASE			,		eos_token=__SCREAMING_SNAKE_CASE			,		unk_token=__SCREAMING_SNAKE_CASE			,		pad_token=__SCREAMING_SNAKE_CASE			,		sp_model_kwargs=self.sp_model_kwargs			,		**__SCREAMING_SNAKE_CASE			,		)

      lowerCamelCase_       	=		vocab_file

      lowerCamelCase_       	=		spm.SentencePieceProcessor(**self.sp_model_kwargs   )
      self.sp_model.Load(__SCREAMING_SNAKE_CASE   )






    @property
    def   UpperCamelCase			(			self	:				Any   )	->						List[Any]:
      return self.sp_model.get_piece_size()






    def   UpperCamelCase			(			self	:				int   )	->						List[str]:
      lowerCamelCase_       	=		{self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE   ): i for i in range(self.vocab_size   )}
      vocab.update(self.added_tokens_encoder   )
      return vocab






    def __getstate__(			self	:				Dict   )	->						Optional[int]:
      lowerCamelCase_       	=		self.__dict__.copy()
      lowerCamelCase_       	=		None
      return state






    def __setstate__(			self	:				str			,		__SCREAMING_SNAKE_CASE	:				List[str]   )	->						Any:
      lowerCamelCase_       	=		d

      # for backward compatibility
      if not hasattr(self			,		'sp_model_kwargs'   ):
        lowerCamelCase_       	=		{}

      lowerCamelCase_       	=		spm.SentencePieceProcessor(**self.sp_model_kwargs   )
      self.sp_model.Load(self.vocab_file   )






    def   UpperCamelCase			(			self	:				Tuple			,		__SCREAMING_SNAKE_CASE	:				str   )	->						List[str]:
      return self.sp_model.encode(__SCREAMING_SNAKE_CASE			,		out_type=__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				str			,		__SCREAMING_SNAKE_CASE	:				str   )	->						Dict:
      return self.sp_model.piece_to_id(__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				Union[str, Any]			,		__SCREAMING_SNAKE_CASE	:				Optional[Any]   )	->						Optional[int]:
      lowerCamelCase_       	=		self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE   )
      return token






    def   UpperCamelCase			(			self	:				List[str]			,		__SCREAMING_SNAKE_CASE	:				List[str]   )	->						Optional[Any]:
      lowerCamelCase_       	=		[]
      lowerCamelCase_       	=		''
      for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
          out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE   ) + token
          lowerCamelCase_       	=		[]
        else:
          current_sub_tokens.append(__SCREAMING_SNAKE_CASE   )
      out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE   )
      return out_string.strip()






    def   UpperCamelCase			(			self	:				Any			,		__SCREAMING_SNAKE_CASE	:				Optional[int]			,		__SCREAMING_SNAKE_CASE	:				Tuple=None   )	->						List[int]:
      if token_ids_a is None:
        return token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return token_ids_a + token_ids_a + [self.eos_token_id]






    def   UpperCamelCase			(			self	:				Any			,		__SCREAMING_SNAKE_CASE	:				List[int]			,		__SCREAMING_SNAKE_CASE	:				Optional[List[int]] = None			,		__SCREAMING_SNAKE_CASE	:				bool = False   )	->						List[int]:
      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__SCREAMING_SNAKE_CASE			,		token_ids_a=__SCREAMING_SNAKE_CASE			,		already_has_special_tokens=__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		[1]
      if token_ids_a is None:
        return ([0] * len(__SCREAMING_SNAKE_CASE   )) + suffix_ones
      return ([0] * len(__SCREAMING_SNAKE_CASE   )) + ([0] * len(__SCREAMING_SNAKE_CASE   )) + suffix_ones






    def   UpperCamelCase			(			self	:				Dict			,		__SCREAMING_SNAKE_CASE	:				str			,		__SCREAMING_SNAKE_CASE	:				Optional[str] = None   )	->						Tuple[str]:
      if not os.path.isdir(__SCREAMING_SNAKE_CASE   ):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
        return
      lowerCamelCase_       	=		os.path.join(
          __SCREAMING_SNAKE_CASE			,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

      if os.path.abspath(self.vocab_file   ) != os.path.abspath(__SCREAMING_SNAKE_CASE   ) and os.path.isfile(self.vocab_file   ):
        copyfile(self.vocab_file			,		__SCREAMING_SNAKE_CASE   )
      elif not os.path.isfile(self.vocab_file   ):
        with open(__SCREAMING_SNAKE_CASE			,		'wb'   ) as fi:
          lowerCamelCase_       	=		self.sp_model.serialized_model_proto()
          fi.write(__SCREAMING_SNAKE_CASE   )

      return (out_vocab_file,)












"""simple docstring"""





def 	lowerCamelCase__			(				_lowerCamelCase			:						list[list[int | float]]					) ->							int:
  lowerCamelCase_       	=		len(_lowerCamelCase					)
  lowerCamelCase_       	=		len(matrix[0]					)
  lowerCamelCase_       	=		min(_lowerCamelCase						,							_lowerCamelCase					)

  for row in range(_lowerCamelCase					):
    # Check if diagonal element is not zero
    if matrix[row][row] != 0:
      # Eliminate all the elements below the diagonal
      for col in range(row + 1						,							_lowerCamelCase					):
        lowerCamelCase_       	=		matrix[col][row] / matrix[row][row]
        for i in range(_lowerCamelCase						,							_lowerCamelCase					):
          matrix[col][i] -= multiplier * matrix[row][i]
    else:
      # Find a non-zero diagonal element to swap rows
      lowerCamelCase_       	=		True
      for i in range(row + 1						,							_lowerCamelCase					):
        if matrix[i][row] != 0:
          lowerCamelCase_	,      lowerCamelCase_       	=		matrix[i], matrix[row]
          lowerCamelCase_       	=		False
          break
      if reduce:
        rank -= 1
        for i in range(_lowerCamelCase					):
          lowerCamelCase_       	=		matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
      row -= 1

  return rank


if __name__ == "__main__":
  import doctest

  doctest.testmod()




